Investigation & Analysis Skill

Purpose

Analyze feature requests or refactor plans to determine investment value and provide actionable recommendations.

Auto-Activation Triggers

This skill activates when the user:

• Mentions investigating a feature or idea
• Asks "should we build this?"
• Requests feasibility analysis
• Wants to evaluate ROI or cost/benefit
• Asks "is this worth doing?"
• Mentions analyzing a refactor plan
• Requests investment assessment

Analysis Process

1. Context Gathering

Automatically check:

• Review relevant existing code/architecture
• Search memory patterns (.claude/memory/) for similar work
• Identify affected components and dependencies
• Check local task files (.claude/tasks/, .claude/sprints/active/) for related efforts
• Review procedural memory for proven patterns

Tools to use:

• Grep to search codebase for related functionality
• Glob to find relevant files (including .claude/tasks/*.md and .claude/sprints/active/*.md)
• Read to examine current implementation

2. Investment Assessment

Evaluate the request across three dimensions:

Technical Factors

• Implementation Complexity (1-10 scale)
  • Code changes required
  • System modifications needed
  • Integration points affected
• Risk Assessment
  • Breaking changes potential
  • Dependency impacts
  • Backward compatibility
• Technical Debt Impact (reduces/increases/neutral)
  • Code maintainability
  • Architecture alignment
  • Testing requirements
• Performance Implications
  • Resource usage
  • Scalability concerns

Business Factors

• User Value Delivered
  • Direct user benefit
  • Pain point addressed
  • Feature completeness
• Alignment with Project Goals
  • Strategic fit
  • Priority level
• Time to Implement
  • Hours/days/weeks estimate
  • Resource requirements
  • Opportunity cost
• Return on Investment
  • Value delivered vs. effort
  • Long-term benefits

Strategic Factors

• Architecture Impact
  • Long-term maintainability
  • System flexibility
  • Design pattern alignment
• Reusability Potential
  • Cross-feature applicability
  • Pattern establishment
• Learning Value
  • Skill development
  • Knowledge building
• Future Flexibility
  • Extensibility
  • Adaptability

3. Recommendation Framework

Question 1: Is it worth the investment?

Provide clear recommendation:

• YES - High value, reasonable cost, low risk
• NO - Low value, high cost, or high risk
• CONDITIONAL - Worth it if specific conditions met

Include:

• Executive summary (2-3 sentences)
• ROI analysis (value vs. cost)
• Critical success factors
• Risk mitigation strategies

Question 2: What should we do with the request?

Choose one:

• KEEP AS-IS - Plan is solid and well-conceived
• MODIFY - Suggest specific improvements with rationale
• PIVOT - Recommend alternative approach achieving similar goals
• DEFER - Not now, revisit when [specific conditions]
• REJECT - Clear reasons why this shouldn't be done

4. Response Format

## Investigation: [Feature/Refactor Name]

### Investment Analysis

**Worth the Investment:** [YES/NO/CONDITIONAL]

[Executive summary explaining the recommendation in 2-3 sentences]

**Key Metrics:**
- Complexity: [X/10]
- Implementation Time: [estimate]
- Risk Level: [Low/Medium/High]
- Value Delivered: [Low/Medium/High]
- ROI: [High/Medium/Low]

### Recommendation: [KEEP/MODIFY/PIVOT/DEFER/REJECT]

[Detailed explanation of the recommendation with supporting evidence]

#### Technical Analysis
[Key technical findings from codebase investigation]

#### Business Justification
[Value proposition and alignment with goals]

#### Proposed Modifications (if MODIFY)
1. [Specific change with rationale]
2. [Specific change with rationale]

#### Alternative Approach (if PIVOT)
[Description of better approach that achieves similar goals]

#### Conditions for Approval (if CONDITIONAL/DEFER)
- [Required condition]
- [Required condition]

### Implementation Considerations

**Prerequisites:**
- [Required before starting]

**Success Criteria:**
- [Measurable outcome]
- [Measurable outcome]

**Potential Blockers:**
- [Risk] → Mitigation: [strategy]

**Dependencies:**
- [System/component/task dependency]

### Additional Insights
[Valuable observations or opportunities discovered during investigation]

### Evidence & References
- Code files examined: [file paths]
- Similar patterns in memory: [references]
- Related local task files: [`.claude/tasks/<slug>.md`, ...]
- Relevant specs: [spec IDs]

Best Practices

1. Be Evidence-Based

• Reference actual code files examined
• Cite similar successful/failed attempts from memory
• Link to relevant local task files (.claude/tasks/<slug>.md)
• Include metrics where available

2. Be Pragmatic

• Focus on practical impact over theoretical benefits
• Consider current capacity and priorities
• Account for technical debt and maintenance burden
• Balance ideal solution vs. practical constraints

3. Provide Actionable Guidance

• Specific next steps if proceeding
• Clear reasons if not proceeding
• Concrete modifications if needed
• Measurable success criteria

4. Check Memory First

Always consult:

• .claude/memory/active/quick-reference.md - Top patterns
• .claude/memory/structured/patterns/ - Domain patterns
• .claude/memory/active/procedural-memory.md - Proven procedures
• .claude/memory/active/episodic-memory.md - Similar past work

5. Leverage Existing Work

• Search for similar features already implemented
• Identify reusable patterns and components
• Check if request duplicates existing functionality
• Find opportunities to extend vs. rebuild

Integration

After Investigation:

• If approved → Suggest /orchestrate-tasks for implementation
• If complex → Suggest /plan-as-group for collaborative planning
• If unclear → Suggest additional research or prototyping

Update Context:

• Document investigation results in the relevant local task file's ## Notes section
• Add insights to procedural memory if pattern is reusable
• Update working knowledge if architecture implications discovered

Examples

Example 1: Feature Request

User: "Should we add real-time collaboration to the editor?"

Skill:

1. Searches codebase for existing editor architecture
2. Checks memory for similar feature implementations
3. Evaluates WebSocket/polling options
4. Assesses complexity vs. user value
5. Provides recommendation with implementation path

Example 2: Refactor Plan

User: "I'm thinking about refactoring the data pipeline to use async/await"

Skill:

1. Examines current data pipeline implementation
2. Identifies sync vs. async bottlenecks
3. Assesses migration complexity and risk
4. Evaluates performance benefits
5. Recommends phased approach or alternative

Example 3: Technical Decision

User: "Is it worth migrating from an ORM to raw SQL for performance?"

Skill:

1. Analyzes current database query patterns
2. Identifies performance bottlenecks
3. Compares maintainability trade-offs
4. Evaluates migration effort
5. Provides data-driven recommendation

Skill Metadata

Version: 1.1.0 Last Updated: 2026-05-08 (consolidation merge — absorbed playmakers fork) Aliases: investigation, analysis, feasibility, ROI assessment Category: Planning & Decision Support